computer-vision-1

Multi-modal image segmentation

3260 papers • 126 benchmarks • 313 datasets

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Most implemented papers

Image Segmentation Using Text and Image Prompts

Alexander S. Ecker, Timo Lüddecke•Fri Dec 17 2021

This work proposes a system that can generate image segmentations based on arbitrary prompts at test time, and builds upon the CLIP model as a backbone which it extends with a transformer-based decoder that enables dense prediction.

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HyperDense-Net: A Hyper-Densely Connected CNN for Multi-Modal Image Segmentation

Christian Desrosiers, Jing Yuan, J. Dolz, Karthik Gopinath, H. Lombaert, Ismail ben Ayed•Sun Apr 08 2018

HyperDenseNet is proposed, a 3-D fully convolutional neural network that extends the definition of dense connectivity to multi-modal segmentation problems and has total freedom to learn more complex combinations between the modalities, within and in-between all the levels of abstraction, which increases significantly the learning representation.

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